Cargando…

Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data

BACKGROUND: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction...

Descripción completa

Detalles Bibliográficos
Autores principales: Baveicy, Kamran, Mostafaei, Shayan, Darbandi, Mitra, Hamzeh, Behrooz, Najafi, Farid, Pasdar, Yahya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102908/
https://www.ncbi.nlm.nih.gov/pubmed/32273739
http://dx.doi.org/10.2147/DMSO.S238153
_version_ 1783511936964493312
author Baveicy, Kamran
Mostafaei, Shayan
Darbandi, Mitra
Hamzeh, Behrooz
Najafi, Farid
Pasdar, Yahya
author_facet Baveicy, Kamran
Mostafaei, Shayan
Darbandi, Mitra
Hamzeh, Behrooz
Najafi, Farid
Pasdar, Yahya
author_sort Baveicy, Kamran
collection PubMed
description BACKGROUND: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS. METHODS: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values. RESULTS: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81–0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85–0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74–0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61–0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47–0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47–0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point. CONCLUSION: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.
format Online
Article
Text
id pubmed-7102908
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-71029082020-04-09 Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data Baveicy, Kamran Mostafaei, Shayan Darbandi, Mitra Hamzeh, Behrooz Najafi, Farid Pasdar, Yahya Diabetes Metab Syndr Obes Original Research BACKGROUND: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS. METHODS: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values. RESULTS: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81–0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85–0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74–0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61–0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47–0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47–0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point. CONCLUSION: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS. Dove 2020-03-24 /pmc/articles/PMC7102908/ /pubmed/32273739 http://dx.doi.org/10.2147/DMSO.S238153 Text en © 2020 Baveicy et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Baveicy, Kamran
Mostafaei, Shayan
Darbandi, Mitra
Hamzeh, Behrooz
Najafi, Farid
Pasdar, Yahya
Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title_full Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title_fullStr Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title_full_unstemmed Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title_short Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data
title_sort predicting metabolic syndrome by visceral adiposity index, body roundness index and a body shape index in adults: a cross-sectional study from the iranian rancd cohort data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102908/
https://www.ncbi.nlm.nih.gov/pubmed/32273739
http://dx.doi.org/10.2147/DMSO.S238153
work_keys_str_mv AT baveicykamran predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata
AT mostafaeishayan predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata
AT darbandimitra predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata
AT hamzehbehrooz predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata
AT najafifarid predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata
AT pasdaryahya predictingmetabolicsyndromebyvisceraladiposityindexbodyroundnessindexandabodyshapeindexinadultsacrosssectionalstudyfromtheiranianrancdcohortdata